GUIDELINE FOR THE IMPLEMENTATION OF AUTONOMOUS SYSTEMS IN MINING

Published: 2019-04-18

Working Group: Autonomous Mining

Status: Current, revision ongoing

Translation available in: Russian 

ABSTRACT

This guideline provides stakeholders with the tools necessary to move forward with implementation of autonomous systems in mining and advance those projects. It should be used as a first step to assist companies implementing autonomous mining projects regardless of the size and scope of project (single autonomous vehicles to highly autonomous). It also provides a high-level framework for mining stakeholders to follow when establishing autonomous mining projects ranging from single autonomous vehicles and hybrid fleets to highly autonomous fleets. It offers guidance on how stakeholders should approach autonomous mining and describes common practices. More specifically, it addresses: 

  • Change management 
  • Developing a business case 
  • Health and safety and risk management 
  • Regulatory engagement 
  • Community and social impact 
  • Operational readiness and deployment. 

CONTINUE COLLABORATING

Success story? Input on how to improve this guideline? Let us know.

To share your experience using the guideline, please fill out this case study form. 

For more general feedback, please fill out the form below:

    FIGURES

    Figure 1. Mining Automation Maturity Model
    Factors Influencing the Choice of Implementation Approach (Figure Design, GMG Contributor)
    Figure 3. Change Management Progression from Preparation to Mature/Steady State (Figure Design, GMG)
    Figure 4. Hierarchy of Controls for Autonomous Mining Systems (Figure Design, GMG)
    Figure 5. Engineering Design Management Framework for Implementing Autonomous Systems (Figure Design, GMG)

    RELATED CASE STUDIES

    Skills migration for remote drill operators
    Transition from haulage technicians to autonomous controllers at Vale
    Rio Tinto's experience with automation improving safety for employees and creating value
    Lessons learned when workforce reduction was a factor in migrating truck drivers to autonomous fleets

    PRESS RELEASE

    RELATED WORK

    EXTERNAL SOURCES

    X